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AI chips are getting so hot, diamonds may be the answer

Chips, memory, energy, and data center space are already in limited supply due to the artificial intelligence development. Something often seen in a jewelry shop could provide its next chance. As hotter processors increase demand for materials that can dissipate heat more quickly, Chinese lab-grown diamond producers are now turning beyond rings and necklaces toward […]

Chips, memory, energy, and data center space are already in limited supply due to the artificial intelligence development.

Something often seen in a jewelry shop could provide its next chance.

As hotter processors increase demand for materials that can dissipate heat more quickly, Chinese lab-grown diamond producers are now turning beyond rings and necklaces toward AI-chip cooling.

Economics may explain the change.

Industrial synthetic diamonds can generate gross margins of about 50%, compared with roughly 30% to 40% for gem-grade diamonds, according to producers interviewed by Reuters.

At the same time, rising Chinese production has driven down the cost of jewelry diamonds, forcing producers to look for new lucrative applications.

That creates an unusual intersection. AI companies need better ways to keep increasingly powerful processors cool. China’s enormous synthetic-diamond industry needs a new growth market. Diamonds could connect the two.

Diamonds could help solve AI’s growing heat problem

Appearance is not the main factor in the appeal. It’s that the diamond is an excellent heat conductor.

Because of its properties, it may be helpful as a heat spreader, transferring focused heat from a processor’s hottest areas to a cooling system.

As AI processors need more power, the issue is becoming increasingly significant.

While data-center owners are investing considerably in technology that can handle higher-density server racks, Nvidia’s latest systems are becoming more and more dependent on liquid cooling.

An early illustration of the potential contribution of diamond was offered by Chinese experts.

In April, a diamond-copper cooling module developed by the Ningbo Institute of Materials Technology & Engineering improved heat transfer from a chip module by 80% and increased chip performance by 10%, according to Reuters.

Additionally, commercial cooling solutions are beginning to use the technique. In October, the Silicon Valley firm Frore Systems introduced LiquidJet Diamond, a liquid-cooling plate that precisely positions diamond over a graphics processor’s hot spots.

Frore Systems claims that compared to traditional cold plates, its design can lower temperatures of graphics processors by 16 to 22 degrees Celsius and increase the number of AI tokens generated per watt by 30% to 35%.

Related: Tesla and Nvidia just found another AI bottleneck

These numbers are not independent test findings; rather, they are business assertions.

According to Frore, the technology is being developed for next CPUs, such as AMD’s MI-series accelerators and Nvidia’s Rubin Ultra.

This development is noteworthy as cooling begins to play a role in performance.

A chip may need to lower its working speed if it can’t effectively dissipate heat. Improved cooling may therefore allow more costly AI technology to operate closer to its intended capabilities for longer periods.

China’s diamond glut is creating a very different AI trade

China already has a huge advantage in lab-grown diamonds. The country produces about half of the global supply, according to Reuters.

About 80% of China’s synthetic diamond manufacturing comes from the province of Henan.

At first, jewelry was a major component of that scale. But some producers now want to alter the composition.

Feng Canjun’s plant currently uses approximately 70% of the 2 million carats of lab-grown diamonds it produces yearly in jewelry. By 2030, he expects industrial and utilitarian materials to make up more than half of output, with jewelry making up no more than 30%.

Another Chinese manufacturer has already made a financial commitment. Reuters reports that Henan Liliang Diamond will redirect 1 billion yuan ($149 million) from gem-diamond production to a functional-diamond project.

The explanation is simple: China’s capacity to produce lab-grown diamonds on a large scale has contributed to the jewelry market’s excess supply, pressuring prices.

AI infrastructure gives manufacturers a path to goods for which performance is more important than whether customers want another diamond ring.

The Shanghai Diamond Exchange exported 1.41 billion yuan, or $210 million, of lab-grown diamonds in the first half of 2026, up 65.3% year over year, according to South China Morning Post.

Replacing the cooling system around a server is not always the greater opportunity.

In such an arrangement, diamond offers an additional layer that helps transmit heat from more concentrated hotspots. This might place it in the same category as thermal management solutions provided by Shin-Etsu Chemical, Henkel, and Dow, Reuters noted.

Diamond heat spreaders may be able to compete with certain current materials if they become widely used.

Nvidia’s hottest chips are creating a new kind of diamond demand.

JOHN MACDOUGALL / Getty Images

Big tech companies are already looking at diamond cooling

This idea has moved beyond laboratory research. Taiwan Semiconductor Manufacturing (TSM) and Huawei are investigating synthetic diamonds for chip cooling, according to Chinese media.

Lenovo claims to employ a diamond-copper cooling material in a laptop it previously introduced in China.

In June, Intel (INTC) CEO Lip-Bu Tan said he had personally invested in Diamond Foundry, a lab-grown diamond startup in the United States that produces diamond wafers for semiconductor applications, Reuters reported.

Intel itself did not announce an investment.

Additionally, investment is shifting outside of China.

In order to build a Diamond Foundry facility in Trujillo that would produce synthetic diamond wafers, the Spanish government is investing 753 million euros, or around $868 million.

In June, Japan’s Orbray and De Beers’ synthetic diamond company, Element Six, said they had created three-inch single-crystal diamond wafers and were getting ready to generate two-inch wafers in Oregon.

These investments do not imply that silicon will soon be replaced by diamond. Instead, they see thermal management as a more immediate possibility.

Because chip applications demand very high purity and precision production, using diamond itself as a semiconductor material is far more challenging. For investors, that difference is important.

Cooling, not diamond processors taking the place of Nvidia GPUs, is the short-term story.

Diamond cooling comes with a China problem

There is another reason this market could become important. A prosperous diamond-cooling sector might result in a new supply-chain reliance due to China’s supremacy.

In 2024, Beijing imposed export restrictions on equipment and parts used in the creation of synthetic diamonds, and in 2025, it expanded its control regime to include additional synthetic diamond items.

Implementation of some measures was later postponed under a U.S.-China agreement, according to Reuters.

More Nvidia:

This brings synthetic diamonds into a well-known technological controversy.

Access to cutting-edge chips, chipmaking machinery, and vital minerals has previously been a source of contention between the United States and China. Diamonds may be added to the list if they are crucial for cooling the next generation of AI computers.

Caution is still warranted, since it is much more difficult to manufacture chip-grade material than jewelry stones.

In comparison to copper and other well-known thermal materials, the price must be reasonable. Additionally, before demand completely emerges, China’s manufacturers may generate another wave of surplus capacity.

However, the plot is intriguing precisely because of this.

There was an overabundance of lab-grown diamonds at the beginning of this cycle. AI also posed a heat challenge.

These two issues could begin to resolve one another if diamond cooling advances from encouraging trials into massive data centers.

Related: Tesla and Nvidia just found another AI bottleneck

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